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标 题: A Data Mesh Approach for Enabling Data-Centric Applications at the Tactical Edge
数据网格方法:在战术边缘实现以数据为中心的应用
作 者: Simon Dahdal
Filippo Poltronieri
Mauro Tortonesi
Cesare Stefanelli
Niranjan Suri
关键词: Tactical networks  [战术网络]
Federation  [ 联邦系统]
Internet of battlefield things (IoBT)  [ 战场物联网(IoBT)]
Big data  [ 大数据]
Machine learning  [ 机器学习]
出版年: 2023
文集名: 2023 International Conference on Military Communications and Information Systems (ICMCIS 2023)
2023年国际军事通信与信息系统会议(ICMCIS 2023)
会议名: 2023 International Conference on Military Communications and Information Systems (ICMCIS 2023)
2023年国际军事通信与信息系统会议(ICMCIS 2023)
届 次:
摘 要: Effectively managing, sharing, and analyzing large volumes of data in real time is essential for making informed decisions, predicting potential threats, and adapting to changes on the battlefield. It therefore represents a critical capability for military operations. However, implementing effective analytics at the tactical edge requires to address the challenges of Denied, Degraded, Intermittent, and Limited (DDIL) networks, particularly in terms of bandwidth and processing capability constraints. Additionally, implementing such a system presents other challenges such as ensuring the security, trustworthiness, integrity, and privacy of data in motion and at rest. The accurate analysis of the vast amounts of data generated at the tactical edge requires a dedicated IT infrastructure shareable designed to operate in an unpredictable and changing environment while still ensuring the availability and reliability of the data. To address these challenges, we propose a middleware architecture based on a data mesh approach, which is designed to adapt to the demands of modern tactical networks by providing a secure and efficient data-centric storage solution for (big) data. Our proposed middleware is based on a distributed domain-driven approach to serve "data as a product", facilitating data management and analysis, and providing a flexible and robust solution for developing data-driven services. "This paper was originally presented at the NATO Science and Technology Organization Symposium (ICMCIS) organized by the Information Systems Technology (IST) Panel, IST-200RSY - the ICMCIS, held in Skopje, North Macedonia, 16-17 May 2023".

实时有效地管理、共享和分析海量数据,对于做出明智决策、预测潜在威胁以及应对战场上的变化至关重要,因此是军事行动中的关键能力。然而,在战术前沿实施有效的数据分析,必须解决“被阻断、降级、间歇性、受限”(DDIL)网络所面临的挑战,尤其是在带宽和处理能力方面的限制。此外,部署此类系统还面临其他挑战,例如确保数据在传输和静止状态下的安全性、可信度、完整性与隐私性。要准确分析战术前沿产生的海量数据,需要建设一套专用的IT基础设施,该基础设施应具备可共享性,能够在不可预测且不断变化的环境中运行,同时保障数据的可用性和可靠性。为应对这些挑战,我们提出了一种基于数据网格架构的中间件体系结构,旨在通过提供安全高效的以数据为中心的大数据存储解决方案,满足现代战术网络的需求。我们提出的中间件基于分布式领域驱动方法,将“数据作为产品”进行服务,便于数据管理与分析,并为开发数据驱动型服务提供灵活且稳健的解决方案。本文最初发表于2023年5月16日至17日在北马其顿斯科普里举行的北约科学技术组织研讨会(ICMCIS),该会议由信息系统技术(IST)小组主办,IST-200RSY——ICMCIS。
中文内容为网络AI翻译,专业术语未必准确,仅供参考。

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